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New generator creates realistic hospital scheduling data

By PulseAugur Editorial · [1 sources] ·

A new configurable instance generator has been developed for patient-to-room assignment and admission scheduling problems in healthcare. This tool, based on an extensive analysis of real hospital data, aims to improve the realism of generated instances by identifying ward-specific patterns like patient age and length-of-stay distributions. The generator also addresses the issue of infeasible instances by implementing a dynamic programming approach and extending existing feasibility results. AI

RANK_REASON The cluster contains a research paper detailing a new method for generating synthetic data for healthcare optimization problems. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.LG →

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New generator creates realistic hospital scheduling data

COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Tabea Brandt, Christina B\"using, Johanna Leweke, Finn Seesemann, Sina Weber ·

    Instance Generation for Patient-to-room Assignment and Admission Scheduling Based on Real Hospital Data

    arXiv:2507.03423v2 Announce Type: replace-cross Abstract: Developing algorithms for real-life problems that perform well in practice depends on the availability of realistic data for testing. Obtaining real-life data for optimization problems in health care, however, is often dif…

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